Artificial intelligence is making inroads across the insurance sector, yet a new GlobalData poll suggests the industry has not resolved fundamental questions about whether the technology – or the organizations deploying it – can support broad implementation.
The poll, fielded in the first and second quarters of 2026 among 113 respondents, found that close to one in four participants identified AI itself as not ready for widespread use in insurance. Published May 26, the GlobalData findings point to a gap between the pace at which insurers, brokers, and reinsurers are moving to integrate AI tools and the maturity of the technology and supporting structures around it. Ben Carey-Evans, senior insurance analyst at GlobalData, said the nature of current deployments may explain the hesitation. “This might be because use cases to date are largely around customer service and chatbots, rather than full-scale implementation. Regulation has not fully caught up yet, and there is concern around who is liable for mistakes made by AI,” Carey-Evans said. The observation points to a practical tension in the market: insurers face competitive pressure to move quickly on AI, while the legal and regulatory scaffolding that would clarify liability in the event of AI-driven errors has yet to be established.
The second-most cited concern in the poll was a lack of AI expertise at the organizational level – a finding that reflects how quickly the technology has moved relative to workforce development across the industry. One notable pattern in the data was the relative confidence respondents expressed in consumers compared to their own organizations. Only 5.3% of respondents pointed to consumer understanding as the primary obstacle to AI adoption. Carey-Evans tied this to the broader consumer environment. “This is likely because consumers are seeing increased usage of AI across all industries and companies they interact with and are becoming accustomed to it,” he said. The contrast is telling: insurance professionals appear more concerned about their own organizations’ capacity to handle AI than they are about whether policyholders will accept it.
Hiring data from GlobalData’s Job Analytics unit offers a window into how the industry is attempting to address the expertise shortfall. In 2025, there were 63,293 active job postings tied to AI expertise in insurance – a 50.9% increase over 2024 and the highest annual total on record. The numbers suggest that insurers are turning to the labor market as one mechanism for closing the capability gap, though the data also illustrates the scale of the challenge: AI applications are expanding faster than organizations can recruit and onboard the people needed to manage them.
Carey-Evans said incremental deployment – rather than a sweeping, enterprise-wide rollout – may be the more practical course. “There will always be challenges to implement a technology with such high expectations as AI across the value chain. Insurers need to ensure they have the right expertise in place and fully understand the technology. Targeting certain areas at a time, such as customer service, customer acquisition, or claims could help make the scale manageable,” he said.
The readiness concerns identified by GlobalData are part of a wider set of questions the industry is grappling with as AI use deepens. A separate report from Willis, published May 28 as part of its Risk and Resilience Review series, examined how AI integration across underwriting, claims, and cyber defense is generating new exposures around accountability and insurability. The Willis report noted that the insurance market is diverging on how to handle AI-related risk in policy language, with some carriers maintaining traditional wording while others are moving toward coverage that explicitly addresses AI and ties underwriting requirements to governance frameworks.
Spike Lipkin, chief AI officer at Willis, said the governance dimension has become as consequential as the technology itself. “AI is already reshaping the risk landscape in real time, but many organisations are moving forward without fully understanding the systems they rely on. Business leaders need to recognise that this is no longer just a technology issue, but a governance, liability, and trust challenge. Those who stay passive risk falling behind both in resilience and competitiveness. Leaders must be vigilant, challenge outputs, and invest in robust governance frameworks that bring transparency and accountability to how AI is deployed,” Lipkin said.
The picture that emerges from both reports is one of an industry that has moved decisively toward AI adoption without yet establishing the internal controls, regulatory clarity, or workforce depth to manage it at scale. The near-term priority appears to be less about whether to use AI and more about building the organizational infrastructure to use it in a way that contains rather than compounds risk. On that front, Carey-Evans’ recommendation for targeted, phased implementation offers a practical starting point – one that allows carriers to develop expertise and test governance approaches in defined areas before expanding AI use more broadly across the business.
